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Steganalysis of content-adaptive JPEG steganography based on Gauss partial derivative filter bank

[+] Author Affiliations
Yi Zhang, Fenlin Liu, Chunfang Yang, Xiangyang Luo

State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou, Henan, China

Zhengzhou Science and Technology Institute, Zhengzhou, Henan, China

Xiaofeng Song

Xi’an Communication Institute, Xi’an, Shanxi, China

Jicang Lu

Zhengzhou Science and Technology Institute, Zhengzhou, Henan, China

J. Electron. Imaging. 26(1), 013011 (Feb 08, 2017). doi:10.1117/1.JEI.26.1.013011
History: Received November 16, 2016; Accepted January 12, 2017
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Abstract.  A steganalysis feature extraction method based on Gauss partial derivative filter bank is proposed in this paper to improve the detection performance for content-adaptive JPEG steganography. Considering that the embedding changes of content-adaptive steganographic schemes are performed in the texture and edge regions, the proposed method generates filtered images comprising rich texture and edge information using Gauss partial derivative filter bank, and histograms of absolute values of filtered subimages are extracted as steganalysis features. Gauss partial derivative filter bank can represent texture and edge information in multiple orientations with less computation load than conventional methods and prevent redundancy in different filtered images. These two properties are beneficial in the extraction of low-complexity sensitive features. The results of experiments conducted on three selected modern JPEG steganographic schemes—uniform embedding distortion, JPEG universal wavelet relative distortion, and side-informed UNIWARD—indicate that the proposed feature set is superior to the prior art feature sets—discrete cosine transform residual, phase aware rich model, and Gabor filter residual.

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Citation

Yi Zhang ; Fenlin Liu ; Chunfang Yang ; Xiangyang Luo ; Xiaofeng Song, et al.
"Steganalysis of content-adaptive JPEG steganography based on Gauss partial derivative filter bank", J. Electron. Imaging. 26(1), 013011 (Feb 08, 2017). ; http://dx.doi.org/10.1117/1.JEI.26.1.013011


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